Agent-based modeling as organizational and public policy simulators.

Lempert R

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Agent-based modeling as organizational and public policy simulators.

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Agent-based models are an increasingly powerful tool for simulating social systems because they can represent important phenomenon difficult to capture in other mathematical formalisms. But, agent-based models have provided only limited support for policy-making because their distinctive abilities are often most useful in situations where the future is unpredictable. In such situations, the traditional analytic methods for applying simulation models to support decision-making are least effective. Fortunately, new analytic approaches for decision-making under conditions of deep uncertainty-emphasizing large ensembles of model-created scenarios and adaptive policies evaluated with the criteria of robustness, rather than with optimality or efficiency-can unleash the full potential of agent-based policy simulators.

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《Proceedings of the National Academy of Sciences of the United States of America》 |2002年第10期|7195-7196|共2页
作者
Lempert R;
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作者单位

RAND, 1700 Main Street, Santa Monica, CA 90407.;

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收录信息美国《科学引文索引》(SCI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
原文格式 PDF
正文语种英语
中图分类自然科学总论;
关键词
Agent; decision; organizational; Public Policy; SOCIAL; 政府政策;

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7. Buss, Claude A., The United States and the Philippines : Background for Policy, Washington (D.C.), American Enterprise for Public Policy Research, 1977, 156 p. ISBN : 0-8447-3258-3. [O] . Louthood Louise 1980

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机译：最终报告：paGE：policy analytics Generation Engine。

Agent-based modeling as organizational and public policy simulators.

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